Desmatamento em áreas protegidas no estado do Acre

Monografia (graduação)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Florestal, 2016.O modelo tradicional de ocupação agropecuária no Brasil tem contribuído com o aumento do desmatamento na Amazônia. Em tempos mais recentes e de escassez de terras cultiváveis, as Unidades de Conservação têm se tornado alvos mais frequentes de invasores para exploração de madeira e desmatamento ilegal. Tais pressões antrópicas têm sido observadas em todos os Estados que compõem a Amazônia brasileira. O presente estudo buscou fazer uma avaliação detalhada da situação das áreas protegidas no estado do Acre utilizando dados de sensores remotos, identificando áreas críticas que requerem especial atenção em curto e médio prazo. Inicialmente foi avaliada a acurácia dos dados do Programa de Cálculo do Desflorestamento da Amazônia – PRODES, comparando-os com inspeções visuais sobre imagens RapidEye de alta resolução espacial. Os resultados deste estudo indicam que os dados do desmatamento produzidos pelo projeto PRODES apresentam uma acurácia global de 92,7%. Utilizando os dados do PRODES até 2015, observou-se que a as Terras Indígenas no estado do Acre não apresentam problemas relevantes relacionados ao desmatamento. Por outro lado, as Unidades de Conservação RESEX Chico Mendes, RESEX do Alto Tarauacá, ARIE Seringal Nova Esperança e FES do Antimary apresentaram as situações mais críticas de desmatamento naquele Estado. Nestas Unidades de Conservação, as áreas desmatadas até 2012 foram em sua maioria ocupadas por pastagens. O processo de desmatamento aliado ao tipo de uso da terra observado nestas áreas protegidas consideradas mais críticas no estado do Acre revelam uma crescente pressão antrópica nos últimos anos desta análise. Esta pressão é uma grande preocupação ambiental e requer medidas urgentes a fim de evitar a descaracterização ou desvio da finalidade de criação destas áreas. Assim, os resultados do presente estudo podem contribuir para a definição de prioridades e estratégias de conservação ambiental no estado do Acre, evitando o avanço do desmatamento ilegal em área protegidas.The traditional model of agricultural occupation in Brazil has contributed to the increase of Amazon deforestation. In more recent times and shortage of arable land, protected areas have become more frequent targets of attackers to logging and illegal deforestation. Such human pressures have been observed in all states that are part of the Brazilian Amazon. This study aimed to make a detailed assessment of the situation of protected areas in the state of Acre using remote sensing data, identifying critical areas that require special attention in the short and medium term. Initially we assessed the accuracy of the data of the Programa de Cálculo do Desflorestamento da Amazônia - PRODES comparing them with visual inspections on high spatial resolution RapidEye images. The results of this study indicate that the deforestation of the data produced by the PRODES project present an overall accuracy of 92.7%. Using PRODES data by 2015, it was observed that the indigenous lands in the state of Acre do not present significant problems related to deforestation. On the other hand, the Conservation Units RESEX Chico Mendes, RESEX do Alto Tarauacá, ARIE Seringal Nova Esperança and FES do Antimary presented the most critical situations of deforestation in that state. In these protected areas, the areas deforested by 2012 were mostly occupied by pastures. The process of deforestation allied to the type of land use observed in these protected areas considered most critical in the state of Acre reveal increasing human pressure in recent years from this analysis. This pressure is a major environmental concern and requires urgent action to prevent the descaracterization or deviation of the creation of these areas purpose. The present study results may contribute to the definition of priorities and environmental conservation strategies in the state of Acre, avoiding the advance of illegal deforestation in protected area

Long-term Landsat-based monthly burned area dataset for the Brazilian biomes using Deep Learning

Fire is a significant agent of landscape transformation on Earth, and a dynamic and ephemeral process that is challenging to map. Difficulties include the seasonality of native vegetation in areas affected by fire, the high levels of spectral heterogeneity due to the spatial and temporal variability of the burned areas, distinct persistence of the fire signal, increase in cloud and smoke cover surrounding burned areas, and difficulty in detecting understory fire signals. To produce a large-scale time-series of burned area, a robust number of observations and a more efficient sampling strategy is needed. In order to overcome these challenges, we used a novel strategy based on a machine-learning algorithm to map monthly burned areas from 1985 to 2020 using Landsat-based annual quality mosaics retrieved from minimum NBR values. The annual mosaics integrated year-round observations of burned and unburned spectral data (i.e., RED, NIR, SWIR-1, and SWIR-2), and used them to train a Deep Neural Network model, which resulted in annual maps of areas burned by land use type for all six Brazilian biomes. The annual dataset was used to retrieve the frequency of the burned area, while the date on which the minimum NBR was captured in a year, was used to reconstruct 36 years of monthly burned area. Results of this effort indicated that 19.6% (1.6 million km2) of the Brazilian territory was burned from 1985 to 2020, with 61% of this area burned at least once. Most of the burning (83%) occurred between July and October. The Amazon and Cerrado, together, accounted for 85% of the area burned at least once in Brazil. Native vegetation was the land cover most affected by fire, representing 65% of the burned area, while the remaining 35% burned in areas dominated by anthropogenic land uses, mainly pasture. This novel dataset is crucial for understanding the spatial and long-term temporal dynamics of fire regimes that are fundamental for designing appropriate public policies for reducing and controlling fires in Brazil